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Insulin-like growth factor binding protein 2: a core biomarker of left ventricular dysfunction in dilated cardiomyopathy
BACKGROUND: RNA modifications, especially N6-methyladenosine, N1-methyladenosine and 5–methylcytosine, play an important role in the progression of cardiovascular disease. However, its regulatory function in dilated cardiomyopathy (DCM) remains to be undefined. METHODS: In the study, key RNA modific...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10617082/ https://www.ncbi.nlm.nih.gov/pubmed/37904201 http://dx.doi.org/10.1186/s41065-023-00298-5 |
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author | Yu, Wei Gao, Hongli Hu, Tianyang Tan, Xingling Liu, Yiheng Liu, Hongli He, Siming Chen, Zijun Guo, Sheng Huang, Jing |
author_facet | Yu, Wei Gao, Hongli Hu, Tianyang Tan, Xingling Liu, Yiheng Liu, Hongli He, Siming Chen, Zijun Guo, Sheng Huang, Jing |
author_sort | Yu, Wei |
collection | PubMed |
description | BACKGROUND: RNA modifications, especially N6-methyladenosine, N1-methyladenosine and 5–methylcytosine, play an important role in the progression of cardiovascular disease. However, its regulatory function in dilated cardiomyopathy (DCM) remains to be undefined. METHODS: In the study, key RNA modification regulators (RMRs) were screened by three machine learning models. Subsequently, a risk prediction model for DCM was developed and validated based on these important genes, and the diagnostic efficiency of these genes was assessed. Meanwhile, the relevance of these genes to clinical traits was explored. In both animal models and human subjects, the gene with the strongest connection was confirmed. The expression patterns of important genes were investigated using single-cell analysis. RESULTS: A total of 4 key RMRs were identified. The risk prediction models were constructed basing on these genes which showed a good accuracy and sensitivity in both the training and test set. Correlation analysis showed that insulin-like growth factor binding protein 2 (IGFBP2) had the highest correlation with left ventricular ejection fraction (LVEF) (R = -0.49, P = 0.00039). Further validation expression level of IGFBP2 indicated that this gene was significantly upregulated in DCM animal models and patients, and correlation analysis validation showed a significant negative correlation between IGFBP2 and LVEF (R = -0.87; P = 6*10(–5)). Single-cell analysis revealed that this gene was mainly expressed in endothelial cells. CONCLUSION: In conclusion, IGFBP2 is an important biomarker of left ventricular dysfunction in DCM. Future clinical applications could possibly use it as a possible therapeutic target. |
format | Online Article Text |
id | pubmed-10617082 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106170822023-11-01 Insulin-like growth factor binding protein 2: a core biomarker of left ventricular dysfunction in dilated cardiomyopathy Yu, Wei Gao, Hongli Hu, Tianyang Tan, Xingling Liu, Yiheng Liu, Hongli He, Siming Chen, Zijun Guo, Sheng Huang, Jing Hereditas Research BACKGROUND: RNA modifications, especially N6-methyladenosine, N1-methyladenosine and 5–methylcytosine, play an important role in the progression of cardiovascular disease. However, its regulatory function in dilated cardiomyopathy (DCM) remains to be undefined. METHODS: In the study, key RNA modification regulators (RMRs) were screened by three machine learning models. Subsequently, a risk prediction model for DCM was developed and validated based on these important genes, and the diagnostic efficiency of these genes was assessed. Meanwhile, the relevance of these genes to clinical traits was explored. In both animal models and human subjects, the gene with the strongest connection was confirmed. The expression patterns of important genes were investigated using single-cell analysis. RESULTS: A total of 4 key RMRs were identified. The risk prediction models were constructed basing on these genes which showed a good accuracy and sensitivity in both the training and test set. Correlation analysis showed that insulin-like growth factor binding protein 2 (IGFBP2) had the highest correlation with left ventricular ejection fraction (LVEF) (R = -0.49, P = 0.00039). Further validation expression level of IGFBP2 indicated that this gene was significantly upregulated in DCM animal models and patients, and correlation analysis validation showed a significant negative correlation between IGFBP2 and LVEF (R = -0.87; P = 6*10(–5)). Single-cell analysis revealed that this gene was mainly expressed in endothelial cells. CONCLUSION: In conclusion, IGFBP2 is an important biomarker of left ventricular dysfunction in DCM. Future clinical applications could possibly use it as a possible therapeutic target. BioMed Central 2023-10-31 /pmc/articles/PMC10617082/ /pubmed/37904201 http://dx.doi.org/10.1186/s41065-023-00298-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Yu, Wei Gao, Hongli Hu, Tianyang Tan, Xingling Liu, Yiheng Liu, Hongli He, Siming Chen, Zijun Guo, Sheng Huang, Jing Insulin-like growth factor binding protein 2: a core biomarker of left ventricular dysfunction in dilated cardiomyopathy |
title | Insulin-like growth factor binding protein 2: a core biomarker of left ventricular dysfunction in dilated cardiomyopathy |
title_full | Insulin-like growth factor binding protein 2: a core biomarker of left ventricular dysfunction in dilated cardiomyopathy |
title_fullStr | Insulin-like growth factor binding protein 2: a core biomarker of left ventricular dysfunction in dilated cardiomyopathy |
title_full_unstemmed | Insulin-like growth factor binding protein 2: a core biomarker of left ventricular dysfunction in dilated cardiomyopathy |
title_short | Insulin-like growth factor binding protein 2: a core biomarker of left ventricular dysfunction in dilated cardiomyopathy |
title_sort | insulin-like growth factor binding protein 2: a core biomarker of left ventricular dysfunction in dilated cardiomyopathy |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10617082/ https://www.ncbi.nlm.nih.gov/pubmed/37904201 http://dx.doi.org/10.1186/s41065-023-00298-5 |
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